Intelligent Human Resource Information System (i-HRIS): A Holistic Decision Support Framework for HR

Intelligent Human Resource Information System (i-HRIS): A Holistic Decision Support Framework for HR Excellence

Abdul-Kadar Masum1, Loo-See Beh1, Abul-Kalam Azad2, and Kazi Hoque3

1Department of Administrative Studies and Politics, University of Malaya, Malaysia

2Department of Applied Statistics, University of Malaya, Malaysia

3Department of Educational Management, Planning and Policy, University of Malaya, Malaysia

Abstract: Nowadays, Human Resource Information System (HRIS) plays a strategic role in the decision making process for effective and efficient Human Resource Management (HRM). For Human Resource (HR) decision making, most of the researchers propose expert systems or knowledge-based systems. Unfortunately, there are some limitations in both of expert system and knowledge-based system. In this paper, we have proposed a framework of Intelligent Human Resource Information System (i-HRIS) applying Intelligent Decision Support System (IDSS) along with Knowledge Discovery in Database (KDD) to improve structured, especially semistructured and unstructured HR decision making process. Moreover, the proposed HR IDSS stores and processes information with a set of Artificial Intelligent (AI) tools such as knowledge-based reasoning, machine learning and others. These AI tools are used to discover useful information or knowledge from past data and experience to support decision making process. We have likewise attempted to investigate IDSS applications for HR problems applying hybrid intelligent techniques such as machine learning and knowledge-based approach for new knowledge extraction and prediction. In summation, the proposed framework consists of input subsystems, decision making subsystems and output subsystems with ten HR application modules.

Keywords: HRIS, KDD, DSS, framework.

Received October 1, 2014; accepted August 12, 2015

 Full text  


  

Read 2437 times Last modified on Monday, 21 May 2018 03:25
Share
Top
We use cookies to improve our website. By continuing to use this website, you are giving consent to cookies being used. More details…